Big Query Admin

Position: Big query Admin

Location: Ashburn, VA (onsite)

Technical Skills

∙ Google Cloud Platform (Google Cloud Platform)

∙ BigQuery Administration & Performance Tuning

∙ BigQuery Reservations & Capacity Management

∙ Python Programming

∙ Google Cloud Platform IAM & Security

∙ Cloud Monitoring & Logging

∙ Cloud Storage

∙ Data Warehousing Concepts

∙ SQL Performance Optimization

∙ Shell Scripting

∙ Terraform

∙ Git / CI-CD Pipelines

∙ Apache Airflow / Cloud Composer (preferred)

Database Knowledge

∙ BigQuery

∙ Teradata (Preferred)

∙ PostgreSQL/MSSQL/Oracle (Good to Have)

Monitoring & Operations

∙ Cloud Monitoring

∙ OpsGenie

∙ Splunk

∙ New Relic

∙ ServiceNow

Job Summary:

The BigQuery Administrator is responsible for the administration, monitoring, performance optimization, security, governance, and operational support of Google Cloud BigQuery environments. The role ensures the availability, scalability, reliability, and cost efficiency of enterprise data platforms while supporting analytics, reporting, AI/ML, and business-critical workloads.

 Support Model: 24x7 Production Support (as applicable)

 Key Responsibilities

Platform Administration

•                     Administer and maintain Google BigQuery environments across Development, QA, UAT, and Production.

•                     Configure and manage datasets, tables, partitions, clustering, and storage lifecycle policies.

•                     Manage BigQuery resource allocation, quotas, reservations, and workload management.

•                     Support platform upgrades, new feature adoption, and environment provisioning.

Performance & Optimization

•                     Analyze and tune BigQuery SQL queries for improved performance and reduced execution cost.

•                     Optimize storage structures, partitioning, clustering, and materialized views.

•                     Monitor query execution patterns and recommend performance improvements.

•                     Improve workload efficiency and reduce cloud spend through continuous optimization.